At a Glance
- Tasks: Lead a team in developing AI solutions and optimising NLP systems.
- Company: Join a cutting-edge Data Science Lab known for innovation and impact.
- Benefits: Enjoy hybrid work, mentorship opportunities, and a culture of continuous learning.
- Other info: Work in Central London, collaborating with diverse teams to solve real-world problems.
- Why this job: Be at the forefront of AI technology, driving product innovation and making a difference.
- Qualifications: PhD or Master's with experience in NLP, software delivery, and applied research leadership.
The predicted salary is between 48000 - 84000 £ per year.
Lead Applied Scientist | Document Understanding • Search • Information Retrieval | London or Switzerland
If you're passionate about pushing the boundaries of NLP, Search and Generative AI, this is an opportunity to work on problems that genuinely haven't been solved at scale.
You'll join a world-class AI research organisation building the document understanding layer that powers next-generation AI search, retrieval and reasoning systems used by millions of professionals globally.
We're hiring across Applied Scientist, Senior Applied Scientist and Lead Applied Scientist levels, so whether you're an established researcher looking to step into technical leadership or already operating as a recognised technical authority, I'd love to speak with you.
You'll tackle challenging problems including:
- Semantic chunking for long, complex documents
- Information extraction and document enrichment
- Knowledge graph construction
- Entity linking and retrieval optimisation
- Synthetic data generation
- Knowledge distillation and efficient production LLM/SLM deployment
The work sits at the intersection of applied research and production engineering—developing state-of-the-art models that rapidly become customer-facing capabilities across multiple AI products.
We're looking for scientists with experience in areas such as:
- NLP & LLMs
- Information Retrieval / Search
- Document Understanding
- Knowledge Graphs
- Information Extraction
- PyTorch, Hugging Face, Python
- Publications in venues such as ACL, EMNLP, NeurIPS, ICLR, SIGIR or KDD are highly valued.
If you're looking for a role where you can build and ship AI solutions at scale in Document Understanding, Search, & Information Retrieval apply today!
Lead Applied Scientist in London employer: Greybridge Search & Selection
At Greybridge Search & Selection, we pride ourselves on being an excellent employer that values innovation and collaboration. Our remote work culture fosters flexibility and inclusivity, allowing you to thrive while leading impactful projects in the Lloyd's insurance sector. With a focus on professional development and a commitment to employee well-being, we offer a supportive environment where your contributions are recognised and rewarded.
Contact Details:
Greybridge Search & Selection Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Lead Applied Scientist in London
✨Tip Number 1
Network with professionals in the NLP and AI fields. Attend industry conferences, webinars, or local meetups to connect with potential colleagues and leaders in the field. This can help you gain insights into the latest trends and possibly get referrals.
✨Tip Number 2
Showcase your expertise by contributing to open-source projects or publishing research papers. This not only demonstrates your skills but also highlights your commitment to the field, making you a more attractive candidate for the Lead Applied Scientist role.
✨Tip Number 3
Prepare to discuss your experience in leading teams and projects. Be ready to share specific examples of how you've driven innovation and collaboration in previous roles, as this will be crucial for demonstrating your fit for the leadership aspect of the position.
✨Tip Number 4
Familiarise yourself with the latest advancements in GenAI and information retrieval techniques. Being knowledgeable about current technologies and methodologies will help you engage in meaningful discussions during interviews and show that you're proactive about staying updated.
We think you need these skills to ace Lead Applied Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in NLP, machine learning, and information retrieval. Include specific projects or roles where you've demonstrated these skills, especially in a commercial context.
Craft a Compelling Cover Letter:In your cover letter, express your passion for AI and how your background aligns with the responsibilities of the Lead Applied Scientist role. Mention your experience leading teams and driving stakeholder engagement.
Showcase Relevant Projects:Include examples of past projects that demonstrate your ability to translate complex problems into successful AI applications. Highlight any published research or intellectual property that showcases your expertise.
Prepare for Technical Questions:Anticipate technical questions related to NLP, model training, and software delivery. Be ready to discuss your hands-on experience and how you approach problem-solving in an applied research setting.
How to prepare for a job interview at Greybridge Search & Selection
✨Showcase Your Technical Expertise
As a Lead Applied Scientist, it's crucial to demonstrate your deep understanding of NLP and information retrieval. Be prepared to discuss specific projects where you've applied these skills, including the challenges you faced and how you overcame them.
✨Highlight Leadership Experience
Since this role involves leading a team, share examples of how you've successfully managed and mentored others in previous positions. Discuss your approach to fostering collaboration and innovation within your team.
✨Align with Business Objectives
Be ready to explain how your technical work has aligned with business goals in the past. This could involve discussing how you've driven product innovation or improved customer satisfaction through your AI solutions.
✨Prepare for Stakeholder Engagement
Expect questions about how you engage with various stakeholders, such as Product and Engineering teams. Prepare examples that illustrate your ability to communicate complex ideas clearly and work collaboratively in an agile environment.
